diff --git a/weather.py b/weather.py
new file mode 100644
index 0000000..8c41951
--- /dev/null
+++ b/weather.py
@@ -0,0 +1,113 @@
+import requests
+from lxml import etree
+import csv
+from collections import Counter
+import pandas as pd
+import matplotlib.pyplot as plt
+
+
+def getweather(url):
+    weather_info = []
+    high_temps = []  # 存储最高气温
+    low_temps = []  # 存储最低气温
+    weather_conditions = []
+    headers = {
+        'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:109.0) Gecko/20100101 Firefox/114.0'
+    }
+
+    response = requests.get(url, headers=headers)
+    html_resp = etree.HTML(response.text)
+    resp_list = html_resp.xpath("//ul[@class='thrui']/li")
+    for li in resp_list:
+        day_weather_info = {}
+        day_weather_info['date_time'] = li.xpath('./div[1]/text()')[0].split(' ')[0]
+        high = li.xpath('./div[2]/text()')[0]
+        high_temp = float(high[:high.find('C')])
+        day_weather_info['high'] = high_temp
+        high_temps.append(high_temp)
+        low = li.xpath('./div[3]/text()')[0]
+        low_temp = float(low[:low.find('C')])
+        day_weather_info['low'] = low_temp
+        low_temps.append(low_temp)
+        day_weather = li.xpath('./div[4]/text()')[0]
+        day_weather_info['weather'] = day_weather
+        weather_conditions.append(day_weather)
+        weather_info.append(day_weather_info)
+
+    return weather_info, high_temps, low_temps, weather_conditions
+
+
+weathers = []
+high_temps = []
+low_temps = []
+weather_conditions = []
+
+for month in range(1, 13):
+    weather_time = '2022' + ('0' + str(month) if month < 10 else str(month))
+    url = f'https://lishi.tianqi.com/guilin/{weather_time}.html'
+    weather, highs, lows, conditions = getweather(url)
+    weathers.append(weather)
+    high_temps.extend(highs)
+    low_temps.extend(lows)
+    weather_conditions.extend(conditions)
+
+with open('weather.csv', 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerow(['日期', '最高气温', '最低气温', '天气'])
+    writer.writerows(
+        [list(day_weather_dict.values()) for month_weather in weathers for day_weather_dict in month_weather])
+
+    weather_counts = Counter(weather_conditions)
+
+    writer.writerow([])
+    writer.writerow(['天气状况', '出现次数'])
+    writer.writerows(weather_counts.items())
+
+
+def plot_weather_counts(weather_counts):
+    df = pd.DataFrame(list(weather_counts.items()), columns=['天气状况', '出现次数'])
+
+    plt.rcParams['font.sans-serif'] = ['SimHei']
+
+    bar_width = 0.5  # 设置柱子的宽度
+    bar_spacing = 0.3  # 设置柱子之间的间隔
+
+    x_positions = range(len(df['天气状况']))  # 设置x轴位置
+    plt.bar(x_positions, df['出现次数'], width=bar_width)
+    plt.xlabel('天气状况')
+    plt.ylabel('出现次数')
+    plt.title('天气状况统计')
+    plt.xticks(x_positions, df['天气状况'], rotation=45, ha='right')  # 设置x轴标签
+
+
+def plot_average_temperatures(high_temps, low_temps):
+    avg_high_temps = [sum(high_temps[i:i + 30]) / len(high_temps[i:i + 30]) for i in range(0, len(high_temps), 30)]
+    avg_low_temps = [sum(low_temps[i:i + 30]) / len(low_temps[i:i + 30]) for i in range(0, len(low_temps), 30)]
+
+    plt.rcParams['font.sans-serif'] = ['SimHei']
+
+    months = range(1, 13)
+    plt.plot(months[:len(avg_high_temps)], avg_high_temps, marker='o', label='平均最高气温')
+    plt.plot(months[:len(avg_low_temps)], avg_low_temps, marker='o', label='平均最低气温')
+
+    plt.xlabel('月份')
+    plt.ylabel('平均气温')
+    plt.title('每月平均气温')
+    plt.xticks(months)
+    plt.legend()
+
+
+# 创建第一个图表，并绘制天气情况柱状图
+fig1, ax1 = plt.subplots()
+plot_weather_counts(weather_counts)
+ax1.set_ylabel('出现次数')
+ax1.set_title('天气状况统计')
+
+# 创建第二个图表，并绘制平均气温折线图
+fig2, ax2 = plt.subplots()
+plot_average_temperatures(high_temps, low_temps)
+ax2.set_xlabel('月份')
+ax2.set_ylabel('平均气温')
+ax2.set_title('每月平均气温')
+
+plt.show()